SYSTEM FOR RECOGNIZING A FORGED AND ALTERED FACE USING GABOR FEATURE AND A SUPPORT VECTOR MACHINE (SVM) CLASSIFICATION MACHINE AND A METHOD THEREOF, CAPABLE OF DETECTING FACE AREA ACCURATELY EVEN TOUGH A PART OF THE FACE IS HIDDEN

摘要

PURPOSE: A system for recognizing a forged and altered face using gabor feature and a support vector machine (SVM) classification machine and a method thereof are provided to recognize the face efficiently as to peripheral lighting influence or various patterns of the face, by estimating feature point positions of the face from the face area and extracting the gabor feature from the estimated face feature points and using the gabor feature as an input vector of the SVM classification machine.;CONSTITUTION: A graph generation unit (100) generates a standard face graph from face image samples. A support vector machine (SVM) learning unit (200) determines an optimum classification plane to discriminate a forged and altered face from face image samples and forged and altered face image samples. A face recognition unit (300) determines forgery of an inputted face image, using the optimum classification plane. The face recognition unit detects a rectangular face area from the face image, and normalizes the rectangular face area into a fixed size, and generates an optimum face graph, using adaboost algorithm.;COPYRIGHT KIPO 2013;[Reference numerals] (100) Graph generation unit; (200) SVM learning unit; (300) Face recognition unit